Research Project
8904902
? DESCRIPTION (provided by applicant): The two dominant preclinical molecular imaging techniques, optical imaging and nuclear imaging, have technical limitations that hamper their use in applications requiring high resolution, longitudinal tracer imaging with absolute quantitation. We are developing a new molecular imaging modality, Magnetic Particle Imaging (MPI), which does not have these limitations and is capable of: nanomolar sensitivity, absolute quantitation of a tracer, resolution independent of depth, and monitoring a stable tracer for weeks to months. These capabilities make MPI complementary to existing molecular imaging techniques and give scientists a versatile new tool when imaging cancer, tracking therapeutic and immune cells, and imaging the cardiovascular system. MPI is best compared with nuclear medicine, in that both modalities see only the injected tracer, both modalities can see right through background tissue, and both modalities are translatable. The MPI technique works by directly detecting the nonlinear magnetization of iron-oxide tracers using low-frequency magnetic fields. MPI's method of direct detection is exquisitely sensitive and we have already demonstrated nanomolar sensitivities in prototype systems. Indeed, the theoretical sensitivity limit of MPI may be as low as a single tagged cell in a voxel. MPI is unrelated to Magnetic Resonance Imaging (MRI), and MPI scans cannot be acquired using a MRI imager. This project aims to develop the first MPI system tailored for pre-clinical researchers working with mouse and rat models. The proposed system will be the world's highest sensitivity and highest resolution tomographic MPI scanner, as well as the first MPI system with integrated CT. First, we will build a high strength field free line magnetic field gradient mounted to a rotating gantry o enable tomographic MPI imaging. We will then integrate CT to enable acquisition of a tissue reference image. Last, we will test the imager on phantoms and post mortem animals.
